Interspeech'2005 - Eurospeech

Lisbon, Portugal
September 4-8, 2005

Speech Extraction in a Car Interior Using Frequency-Domain ICA with Rapid Filter Adaptations

Daisuke Saitoh (1), Atsunobu Kaminuma (1), Hiroshi Saruwatari (2), Tsuyoki Nishikawa (2), Akinobu Lee (2)

(1) Nissan Motor Co. Ltd., Japan; (2) Nara Institute of Science and Technology, Japan

This paper describes two new algorithms for blind source separation (BSS) based on frequency-domain independent component analysis (FDICA). One is FDICA with pre-filtering by a speech sub-band passing filter to slow down the learning speed in low signal-to-noise ratio (SNR) sub-bands. The other is FDICA with sub-band selection learning to reduce the number of iterations for those sub-bands. The results of speech recognition experiments show that each method can improve word accuracy by as much as 7% and that the second method can increase the speed by approximately 60%.

Full Paper

Bibliographic reference.  Saitoh, Daisuke / Kaminuma, Atsunobu / Saruwatari, Hiroshi / Nishikawa, Tsuyoki / Lee, Akinobu (2005): "Speech extraction in a car interior using frequency-domain ICA with rapid filter adaptations", In INTERSPEECH-2005, 2301-2304.